When filling missing values with `ui.rich_text` (i.e. in experiments show CMD), those values were not being correctly matched against `self._fill_value`)
Adds new argument `fill_value` to ParallelCoordinatesRenderer.
For scalar columns, prevent converting to categorical by explictly inserting None when value is missing (value == fill_value).
For categorical columns, replace `fill_value` with `"Missing"` and ensure it is the last item so it gets rendered on top of the column.
Borrowed this idea from pandas api. Current dropna methods will drop a
column or row if any data is missing. But it is also quite useful to
drop those columns or rows only if all of its elements are missing. This
is mostly used for pruning a table.
This method mimics pandas `drop_duplicates` when axis=rows.
For axis=cols this method will drop columns with 0-variance (only
1 unique value). NaNs (`_fill_value`) won't be counted as unique values.
So the following column (`-` would be the `_fill_value`) will be dropped:
foo
-
foo
foo
David de la Iglesia Castro
skshetry
karajan1001
Saugat Pachhai